Title: Target tracking and recognition of a moving video image based on convolution feature selection

Authors: Jun Wei Yang

Addresses: Sports Art Department, Bengbu Medical College, Bengbu 233000, China

Abstract: In order to overcome the low accuracy of moving video image target tracking and recognition, a method of moving video image target tracking and recognition based on convolution feature selection is proposed. In this method, feature centres are generated according to the distance matrix between feature images, and feature dimensions are compressed. The multi-layer convolution feature is used to train multiple trackers to jointly determine the target state. The weight of the tracker is updated online by the real-time error of the tracker, and the information redundancy and noise between different convolution features are filtered out. The experimental results show that the recall rate is close to 100% of the success rate of the tracker, the recognition error rate is close to 0, and the recognition time is less than 0.5 min, which can effectively improve the recognition accuracy. At the same time, the whole algorithm has strong adaptability.

Keywords: convolution feature selection; moving video image; target tracking; recognition.

DOI: 10.1504/IJBM.2021.114646

International Journal of Biometrics, 2021 Vol.13 No.2/3, pp.180 - 194

Received: 23 Mar 2020
Accepted: 19 May 2020
Published online: 29 Apr 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article